{"id":"W2401914715","doi":"10.1021/acs.iecr.5b02420","title":"Use of Nanoparticle Tracking Analysis for Particle Size Determination of Dispersed Catalyst in Bitumen and Heavy Oil Fractions","year":2015,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Electrostatics and Colloid Interactions","field":"Chemistry","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; University of Calgary","keywords":"Nanomaterial-based catalyst; Particle size; Asphalt; Nanoparticle; Nanoparticle tracking analysis; Catalysis; Particle (ecology); Materials science; Range (aeronautics); Tracking (education); Sample preparation; Chemical engineering; Analytical Chemistry (journal); Nanotechnology; Chemistry; Chromatography; Composite material; Organic chemistry; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005492218,0.0004739399,0.0003965533,0.0009452434,0.0002596408,0.0005311063,0.0003647642,0.0004134548,0.0006233473],"category_scores_gemma":[0.001107113,0.000227206,0.0002943621,0.0004686163,0.0002852124,0.0003759194,0.0003001018,0.0004732483,0.0004331512],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003184947,"about_ca_system_score_gemma":0.0003467723,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00138315,"about_ca_topic_score_gemma":0.003004105,"domain_scores_codex":[0.9994451,0.00007173163,0.00004786872,0.0001836478,0.0002103009,0.00004133293],"domain_scores_gemma":[0.9989616,0.0004588109,0.0001525752,0.0001064306,0.000270563,0.00005006765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003146275,0.000006465574,0.000376603,0.00002789169,0.000005087933,0.00002953384,0.00002570319,0.00008135469,0.9959758,0.00004983567,0.00001472246,0.003375538],"study_design_scores_gemma":[8.858365e-7,0.00003972026,0.0009807515,0.000002903643,0.00001038329,0.00007617906,0.00001638594,0.001389485,0.9970079,0.00003101745,0.0004374783,0.000007019359],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7497292,0.002430282,0.2422451,0.0002112766,0.0001387194,0.0001612343,0.0007309433,0.0007110762,0.003642194],"genre_scores_gemma":[0.8383736,0.001630435,0.154895,0.00008646135,0.00002218542,0.0001411519,0.0004124416,0.0001545463,0.004284074],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00138315,"threshold_uncertainty_score":0.002904654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1481626826550699,"score_gpt":0.360796538811289,"score_spread":0.2126338561562192,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}